Results 171 to 180 of about 2,604,528 (199)
Abstract It is challenging to identify comorbidity patterns and mechanistically investigate disease associations based on health‐related data that are often sparse, large‐scale, and multimodal. Adopting a systems biology approach, embedding‐based algorithms provide a new perspective to examine diseases under a unified framework by mapping diseases into
Tianxin Xu+4 more
wiley +1 more source
Extracting knowledge from customer reviews: an integrated framework for digital platform analytics
Abstract Online review sites play a crucial role in shaping consumer purchasing decisions, making the analysis of customer feedback essential for businesses. Given the complexity of these reviews, often including both quantitative and qualitative data, advanced analytical frameworks are necessary.
Anastasios Kyriakidis+1 more
wiley +1 more source
ABSTRACT Background In the aftermath of the COVID‐19 pandemic, it is critical to reflect holistically on the experiences gained in the past few years. We thus review research on remote mathematics teaching in Pre‐K–12 contexts, utilising Activity Theory as a theoretical lens for research synthesis.
Chung Kwan Lo+5 more
wiley +1 more source
The Picard group in equivariant homotopy theory via stable module categories
Abstract We develop a mechanism of “isotropy separation for compact objects” that explicitly describes an invertible G$G$‐spectrum through its collection of geometric fixed points and gluing data located in certain variants of the stable module category.
Achim Krause
wiley +1 more source
Stochastic COVID‐19 epidemic model incorporating asymptomatic and isolated compartments
This study delves into the intricate dynamics of the COVID‐19 epidemic by extending a deterministic compartmental model incorporating asymptomatic, quarantined and isolated compartments, with a stochastic model capturing the natural randomness of the processes.
Tomás Caraballo+5 more
wiley +1 more source
Abstract Model‐based optimization approaches for monitoring and control, such as model predictive control and optimal state and parameter estimation, have been used successfully for decades in many engineering applications. Models describing the dynamics, constraints, and desired performance criteria are fundamental to model‐based approaches. Thanks to
Johannes Pohlodek+4 more
wiley +1 more source
Magnetic particle capture in high‐gradient magnetic separation: A theoretical and experimental study
Abstract High‐gradient magnetic separation (HGMS) has traditionally been used in mineral processing, with many effective models developed for typically employed rod‐wire shaped matrices. However, its potential in bioprocessing, especially for high‐value products, introduces new demands on plant and matrix design. This study presents a multi‐scale model
Marko Tesanovic+3 more
wiley +1 more source
Abstract Distillation is widely used for separating liquid mixtures, but its high heating demand poses challenges for achieving net‐zero emissions. This study presents an innovative approach to electrifying distillation for load adaptability and flexible operation, aligning with dynamic electricity markets driven by renewables.
Meng Qi+5 more
wiley +1 more source
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